1. Technical Field
The present invention relates generally to semiconductor technology and more specifically to semiconductor research and development.
2. Background Art
At the present time, electronic products are used in almost every aspect of life, and the heart of these electronic products is the integrated circuit. Integrated circuits are used in a wide variety of products, such as televisions, telephones, and appliances.
Integrated circuits are made in and on silicon wafers by extremely complex systems that require the coordination of hundreds or even thousands of precisely controlled processes to produce a finished semiconductor wafer. Each finished semiconductor wafer has hundreds to tens of thousands of integrated circuits, each worth hundreds or thousands of dollars.
The ideal would be to have every one of the integrated circuits on a wafer functional and within specifications, but because of the sheer numbers of processes and minute variations in the processes, this rarely occurs. “Yield” is the measure of how many “good” integrated circuits there are on a wafer divided by the total number of integrated circuits formed on the wafer divided by the maximum number of possible good integrated circuits on the wafer. A 100% yield is extremely difficult to obtain because minor variations, due to such factors as timing, temperature, and materials, substantially affect a process. Further, one process often affects a number of other processes, often in unpredictable ways.
In a manufacturing environment, the primary purpose of experimentation is to increase the yield. Experiments are performed in-line and at the end of the production line with both production wafers and experimental wafers. However, yield enhancement methodologies in the manufacturing environment produce an abundance of very detailed data for a large number of wafers on processes subject only to minor variations. Major variations in the processes are not possible because of the time and cost of using production equipment and production wafers. Setup times for equipment and processing time can range from weeks to months, and processed wafers can each contain hundreds of thousands of dollars worth of integrated circuits.
The learning cycle for the improvement of systems and processes requires coming up with an idea, formulating a test(s) of the idea, testing the idea to obtain data, studying the data to determine the correctness of the idea, and developing new ideas based on the correctness of the first idea. The faster the correctness of ideas can be determined, the faster new ideas can be developed. Unfortunately, the manufacturing environment provides a slow learning cycle because of manufacturing time and cost.
Recently, the great increase in the complexity of integrated circuit manufacturing processes and the decrease in time between new product conception and market introduction have both created the need for speeding up the learning cycle.
This has been accomplished in part by the unique development of the integrated circuit research and development environment. In this environment, the learning cycle has been greatly speeded up and innovative techniques have been developed that have been extrapolated to high volume manufacturing facilities.
To speed up the learning cycle, processes are speeded up and major variations are made to many processes, but only a few wafers are processed to reduce cost. The research and development environment has resulted in the generation of tremendous amounts of data and analysis for all the different processes and variations. This, in turn, has required a large number of engineers to do the analysis. With more data, the answer always has been to hire more engineers.
However, this is not an acceptable solution for major problems. For example, semiconductor wafers are manufactured in large groups, or lots. At various stages in the manufacturing or fabrication process, decisions must be made about the quality and condition of each lot, in order to determine the subsequent dispositions of the lots.
Unfortunately, engineers in charge of the manufacturing processes must make those decisions with only limited information. For example, defects are often found on wafer lots in early processing stages. It is then necessary to make a determination concerning whether or not those defects will cause problems in subsequent processing, and if so, the nature and importance of those problems. Considering the enormous complexity of the circuit features on semiconductor wafers, the information that is available to the process engineers is typically far too little for such sophisticated determinations. As a consequence, those decisions can end up appearing somewhat like educated guesswork.
What is needed is an analytical tool that can show the process engineers the actual effects of the various defects at subsequent stages of the wafer fabrication process.
Solutions to these problems have been long sought but prior developments have not taught or suggested any solutions and, thus, solutions to these problems have long eluded those skilled in the art.